Today, cloud service levels associated with cloud workloads and the placement of applications onto cloud environments are often manually created and determined. A human decision may be made as to the criticality of a workload, human inspection and determination of possible cloud infrastructures are accomplished, and human direction is necessary to direct workloads to the appropriate infrastructure. Due to increases in analytics capabilities and complexity of organizational IT systems, needs may arise to automate such decisions, inspections, determinations, and directions. The automation may reduce human error possibilities and optimizes the overall infrastructure according to application needs.